wavefrontshaping/pymmf:a8df6f93 – Run with an API on Replicate

Version

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wavefrontshaping /pymmf:a8df6f93

Playground API

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=wavefrontshaping/pymmf

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run wavefrontshaping/pymmf using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "wavefrontshaping/pymmf:a8df6f9393bb0ace7011857c41b24a6e91ca4138e290197e27f87331280d5dd3",
  {
    input: {
      NA: 0.2,
      wl: 1550,
      core_diam: 50,
      n_cladding: 1.45,
      curvature_x: 10,
      is_curvature: "No",
      profile_type: "GRIN"
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run wavefrontshaping/pymmf using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "wavefrontshaping/pymmf:a8df6f9393bb0ace7011857c41b24a6e91ca4138e290197e27f87331280d5dd3",
    input={
        "NA": 0.2,
        "wl": 1550,
        "core_diam": 50,
        "n_cladding": 1.45,
        "curvature_x": 10,
        "is_curvature": "No",
        "profile_type": "GRIN"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run wavefrontshaping/pymmf using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "a8df6f9393bb0ace7011857c41b24a6e91ca4138e290197e27f87331280d5dd3",
    "input": {
      "NA": 0.2,
      "wl": 1550,
      "core_diam": 50,
      "n_cladding": 1.45,
      "curvature_x": 10,
      "is_curvature": "No",
      "profile_type": "GRIN"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/wavefrontshaping/pymmf@sha256:a8df6f9393bb0ace7011857c41b24a6e91ca4138e290197e27f87331280d5dd3 \
  -i 'NA=0.2' \
  -i 'wl=1550' \
  -i 'core_diam=50' \
  -i 'n_cladding=1.45' \
  -i 'curvature_x=10' \
  -i 'is_curvature="No"' \
  -i 'profile_type="GRIN"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 r8.im/wavefrontshaping/pymmf@sha256:a8df6f9393bb0ace7011857c41b24a6e91ca4138e290197e27f87331280d5dd3
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "NA": 0.2,
      "wl": 1550,
      "core_diam": 50,
      "n_cladding": 1.45,
      "curvature_x": 10,
      "is_curvature": "No",
      "profile_type": "GRIN"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

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